Generation and Validation of Teaching Examples Based on Large Language Models

被引:2
|
作者
He, Qing [1 ]
Wang, Yu [1 ]
Rao, Gaoqi [1 ]
机构
[1] Beijing Language & Culture Univ, Beijing, Peoples R China
来源
2024 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING, IALP 2024 | 2024年
关键词
Large Language Model; Example Sentence Generation; Coarse Processing; Fine Processing; Validation Standards;
D O I
10.1109/IALP63756.2024.10661177
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Example sentences serve as a crucial bridge for learners to master language application rules, enhance language skills, and develop a sense of language. These sentences encompass various aspects, including semantics, grammar, and pragmatics, and hold significant importance in the fields of language teaching and publishing. Large Language Model (LLM) have facilitated the construction and development of generative corpora. Empowered by LLM, example sentences are linked with linguistic elements such as parts of speech and meanings. During the generation process, both coarse-grained and fine-grained resources are fully utilized; in the screening process, relevant research findings on example sentences, errors, and corrections are extensively referenced to form screening norms. This approach results in the construction of a generative example sentence corpus that meets educational needs and maintains a high degree of standardization.
引用
收藏
页码:389 / 395
页数:7
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